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Deciding the sale of a life policy in the viatical market: Implications on individual welfare

Author

Listed:
  • Mar Jori
  • Antonio Alegre
  • Carmen Ribas

    (Universitat de Barcelona)

Abstract

In this paper, we present an economic model that allows a terminally ill policy-holder to decide whether or not to sell (part of) the policy in the viatical settlement market. The viatical settlement market emerged in the late 1980s in response to the AIDS epidemic. Nowadays it is part of the large US market in life settlements. The policies traded in the viatical market are those of terminally ill policyholders expected to die within the next two years. The model is discrete and considers only the next two periods (years), since this is the max- imum remaining lifetime of the policyholder. The decisor has an initial wealth and has to share it between his own consumption and the bequests left to his heirs. We rst introduce the expected utility function of our decisor and then use dynamic programming to deduce the strategy that gives higher utility (not selling/selling (part of) the policy at time zero/selling (part of) the policy at time one). The optima depends on the value of the viaticated policy and on some personal parameters of the individual. We nd an analitical expression for the optimal strategy and perform a sensitivity analysis.

Suggested Citation

  • Mar Jori & Antonio Alegre & Carmen Ribas, 2011. "Deciding the sale of a life policy in the viatical market: Implications on individual welfare," Working Papers in Economics 256, Universitat de Barcelona. Espai de Recerca en Economia.
  • Handle: RePEc:bar:bedcje:2011256
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    References listed on IDEAS

    as
    1. Neeraj Sood & Abby Alpert & Jay Bhattacharya, 2005. "Technology, Monopoly, and the Decline of the Viatical Settlements Industry," NBER Working Papers 11164, National Bureau of Economic Research, Inc.
    2. Jay Bhattacharya & Dana Goldman & Neeraj Sood, 2004. "Price Regulation in Secondary Insurance Markets," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 71(4), pages 643-675.
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    More about this item

    JEL classification:

    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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